FET — July 2025 (v4.0.1 Pythia) — Simulated live trading results using the v4.0.1 Pythia model.
Fetch.ai (FET) combines artificial intelligence with blockchain to create autonomous economic agents that perform tasks on behalf of users. As an AI-crypto narrative leader, FET price is heavily influenced by AI sector sentiment and technology developments. The token shows strong momentum during AI hype cycles and has distinct trading patterns that diverge from the broader market during narrative shifts.
Fetch.ai (FET) — clean monthly entry, no carry-over from previous months. Net of trading fees (Bitvavo 0.15% + 0.25%).
Same coin, same period, same data window — different model. All walk-forward validated. v4.0.1 (Pythia) is the current production model; v4.0 (Itzamná) confirmed the statistical edge across 46 coins; v2.5 is the legacy baseline.
Δ-arrows on the counterpart cards show this page minus that version. Higher return / WR = better; smaller (less negative) Max DD = better.
| Year | Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec | Year Σ |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2025 |
+91.0%
15t
|
+92.3%
14t
|
+111.5%
15t
|
+156.9%
14t
|
+143.4%
16t
|
+61.0%
13t
|
+69.3%
12t
|
+46.3%
7t
|
—
|
—
|
—
|
—
|
+19,261.3% |
All months for FET under this model. Click a cell to drill into that month's trade log. Color intensity = magnitude.
How the model performs across the 4 market regimes detected by Omniscius.
| Regime | Trades | Win Rate | Avg PnL | Compounded Return | Avg Hold |
|---|---|---|---|---|---|
| BUBBLE | 10 | 100.0% | +4.11% | +48.74% | 19h |
| BULL | 2 | 100.0% | +5.78% | +11.88% | 1.5d |
All 12 trades executed during this paper trade period.
| Entry | Exit | Entry Price | Exit Price | PnL | Regime | Duration |
|---|---|---|---|---|---|---|
| $0.00 | $0.00 | +5.08% | BULL | 20h | ||
| $0.00 | $0.00 | +6.47% | BULL | 2.3d | ||
| $0.00 | $0.00 | +7.52% | BUBBLE | 1.3d | ||
| $0.00 | $0.00 | +12.47% | BUBBLE | 1.9d | ||
| $0.00 | $0.00 | +2.38% | BUBBLE | 18h | ||
| $0.00 | $0.00 | +5.47% | BUBBLE | 6h | ||
| $0.00 | $0.00 | +3.61% | BUBBLE | 15h | ||
| $0.00 | $0.00 | +2.28% | BUBBLE | 5h | ||
| $0.00 | $0.00 | +2.93% | BUBBLE | 1.7d | ||
| $0.00 | $0.00 | +0.24% | BUBBLE | 4h | ||
| $0.00 | $0.00 | +0.16% | BUBBLE | 3h | ||
| $0.00 | $0.00 | +4.01% | BUBBLE | 22h |
A paper trade simulates real signal execution without real money. Each month starts fresh with a clean €10,000 allocation — no carry-over from previous months. This shows exactly what would have happened if you started following signals on day one of that month. View live FET signals →
Yes. All results are net of trading fees based on Bitvavo rates (0.15% entry + 0.25% exit). No slippage is applied. Trading via Bitget (0.1%/0.1%) would improve returns.
Paper trades use the same model and signals as the full backtest. The difference: backtests cover years of data across multiple market cycles, while paper trades show month-by-month performance in recent market conditions. Together they provide a complete picture.
Yes. The Omniscius model is retrained bi-weekly, which means paper trade results reflect the exact same model updates that live subscribers receive. This is not a static backtest — it is a living simulation. Learn about Omniscius →
These paper trade results show what our model delivers. Get real-time FET signals with entry, stop-loss, and take-profit on every trade.
Institutional-grade AI trading signals for crypto traders. Our Omniscius v4.2 ensemble model is walk-forward validated across 87 coins and 25,039+ backtested trades. No curve-fitting, no hype — just data-driven signals delivered to your Telegram.
Prices delayed up to 5 minutes. Trading and investing involve significant risk of loss. All content on this site is for informational purposes only and does not constitute financial advice. Decisions to buy, sell, or hold are best made with the advice of qualified financial professionals. Past performance does not guarantee future results.
Hypothetical or simulated performance results have inherent limitations. Unlike an actual performance record, simulated results do not represent actual trading. Since the trades have not been executed, the results may have under- or over-compensated for the impact of certain market factors, including lack of liquidity. No representation is being made that any account will or is likely to achieve profit or losses similar to those shown.
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